Category Archives: Technology

Chiu, a graduate of the Royal College of Art in London, developed Phabit – a “smart pot” that will nurture a plant, depending on whether or not you stick to your habit.

There’s actually some nuance to it. Users of the app complete a personality quiz that puts them into one of four buckets: obliger, questioner, rebel, and upholder. The idea being that the app will challenge each group of people differently.

On its face, it certainly seems like an innovative way to help us form better habits. However, I’m not sure how I feel about the idea of “holding something hostage,” especially another lifeform. I realize that to some, it’s just a plant, but there’s a growing body of evidence substantiating the sentience of plants.

Plant sentience aside (for the moment), let’s look at it purely from a habit forming perspective. Recall from Charles Duhigg’s excellent book, The Power of Habit:

Studies have shown that if you can diagnose your habits, you can change them in whichever way you want.

That’s really important because this thinking wasn’t always the case. Sometimes, folks will tell you that you need to focus on the cue, while others will say you need to focus on the reward. As Duhigg suggests, you can focus on whichever aspect you want, so long as you’ve diagnosed the habit.

Now returning to Phabit – do you think seeing a wilted plant on your desk would raise your level of awareness, with regard to your shirking your goals? If I had to say, I’m probably going to guess the answer is yes. So, purely from a “science of habits”-perspective, Phabit certainly seems like it’s a great way to get people thinking about their habits.

Let’s revisit the plant sentience aspect.

If we presume that plants are sentient (and the evidence certainly points in that direction), then we must consider the ramifications of literally holding another life hostage to our actions. There are two possible outcomes I want to mention: empathy and PTSD.

Empathy. One might argue that by subjecting one’s self to this could foster a sense of empathy (i.e. I feel bad because *I’m* hurting the plant). One might also argue that the “continued killing of plants” (through not completing one’s daily goals) could potentially promote emotional numbing and maybe begin to strip someone of their empathy.

PTSD. Dovetailing with the point on empathy above, I suppose it’s possible that someone might begin to exhibit symptoms of post-traumatic stress from “killing” a plant (or multiple plants, depending on how things go). I realize that this might sound absurd in the abstract, but if we presume plant sentience, killing a plant would fall on the same continuum as killing another being. Granted, the ramifications to one’s psychological wellbeing might not be as severe as if one were to kill an animal or another human being, but when we invent things, it’s incumbent upon us to consider the possible ramifications from as many sides as possible.

A few weeks ago, Tim Harford wrote an excellent article in the Financial Times – what we get wrong about technology. It’s chock-full of things worth considering. For instance, in the opening paragraph, Harford reminds us of a scene from the sci-fi movie Blade Runner. In particular, he draws our attention to the disparateness of having such sophisticated technology that a robot is indistinguishable from a human [Rachael, for those that remember the 1980s classic!], but people still use payphones for communication [Emphasis Added]:

There is something revealing about the contrast between the two technologies — the biotech miracle that is Rachael, and the graffiti-scrawled videophone that Deckard uses to talk to her. It’s not simply that Blade Runner fumbled its futurism by failing to anticipate the smartphone. That’s a forgivable slip, and Blade Runner is hardly the only film to make it. It’s that, when asked to think about how new inventions might shape the future, our imaginations tend to leap to technologies that are sophisticated beyond comprehension.

Later on, Harford reviews the revolutionary invention of the printing press. As it happens, the printing press might have gone the way of the EV1, if not for another invention [Emphasis Added]:

But it would have been a Rachael — an isolated technological miracle, admirable for its ingenuity but leaving barely a ripple on the wider world — had it not been for a cheap and humble invention that is far more easily and often overlooked: paper.

The printing press didn’t require paper for technical reasons, but for economic ones. Gutenberg also printed a few copies of his Bible on parchment, the animal-skin product that had long served the needs of European scribes. But parchment was expensive — 250 sheep were required for a single book. When hardly anyone could read or write, that had not much mattered.

Paper had been invented 1,500 years earlier in China and long used in the Arabic world, where literacy was common. Yet it had taken centuries to spread to Christian Europe, because illiterate Europe no more needed a cheap writing surface than it needed a cheap metal to make crowns and sceptres. Paper caught on only when a commercial class started to need an everyday writing surface for contracts and accounts.

It has to make you wonder… what have we already invented today that will be necessary for the success of a “revolutionary” invention that’s yet to come?

Toilet paper seems a long way from the printing revolution. And it is easily overlooked — as we occasionally discover in moments of inconvenience. But many world-changing inventions hide in plain sight in much the same way — too cheap to remark on, even as they quietly reorder everything. We might call this the “toilet-paper principle”.

Harford goes on to recount many instances of the ‘toilet-paper principle’ in action. He cites barbed wire as the reason for settlers to invest in their land, where previously they had no way of cost-effectively keeping things in (or keeping things out). This quote is particularly apt:

It takes a visionary to see how toilet-paper inventions can totally reshape systems; it’s easier for our limited imaginations to slot Rachael-like inventions into existing systems.

While we’re busy imagining life with flying cars or teleportation, I wonder what innovations we’re missing that are hiding in plain sight.

There’s no question that “data science” is becoming more and more popular. In fact, Booz Allen Hamilton (a consultancy) found:

The term Data Science appeared in the computer science literature throughout the 1960s-1980s. It was not until the late 1990s, however, that the field as we describe it here, began to emerge from the statistics and data mining communities. Data Science was first introduced as an independent discipline in 2001. Since that time, there have been countless articles advancing the discipline, culminating with Data Scientist being declared the sexiest job of the 21st century.

Unsurprisingly, there are countless graduate and undergraduate programs in data science (Harvard, Berkeley, Waterloo, etc.), but what is data science, exactly?

Given that the field is still in its proverbial infancy, there are a number of different perspectives. Booz Allen offers the following in their Field Guide to Data Sciencefrom 2015: “Describing Data Science is like trying to describe a sunset — it should be easy, but somehow capturing the words is impossible.”

Pithiness aside, there does seem to be consensus around some of the pertinent themes contained within data science. For instance, a key component is usually “Big Data” (both unstructured and structured data). Dovetailing with Big Data, “statistics” is often cited as an important component. In particular, an understanding of the science of statistics (hypothesis-testing, etc.), including the ability to manipulate data and almost always — the ability to turn that data into something that non-data scientists can understand (i.e. charts, graphs, etc.). The other big component is “programming.” Given the size of the datasets, Excel often isn’t the best option for interacting with the data. As a result, most data scientists need to have their programming skills up to snuff (often times in more than one language).

What’s a Data Scientist?

Now that we know the three major components of data science are statistics, programming, and data visualization, do you think you could identify data scientists from statisticians, programmers, or data visualization experts? It’s a trick question — they’re all data scientists (broadly speaking).

A few years ago, O’Reilly Media conducted research on data scientists:

Why do people use the term “data scientist” to describe all of these professionals?

[…]

We think that terms like “data scientist,” “analytics,” and “big data” are the result of what one might call a “buzzword meat grinder.” The people doing this work used to come from more traditional and established fields: statistics, machine learning, databases, operations research, business intelligence, social or physical sciences, and more. All of those professions have clear expectations about what a practitioner is able to do (and not do), substantial communities, and well-defined educational and career paths, including specializations based on the intersection of available skill sets and market needs. This is not yet true of the new buzzwords. Instead, ambiguity reigns, leading to impaired communication (Grice, 1975) and failures to efficiently match talent to projects.

So… the ambiguity in understanding the meaning of data science stems from a failure to communicate? Classic movie references aside, the research from O’Reilly identified four main “clusters” of data scientists (and roles within said “clusters”):

Within these clusters fits some of the components described earlier, including two additional components: math/operations research (including things like algorithms and simulations) and business (including things like product development, management, and budgeting). The graphic below demonstrates the t-shaped-nature of data scientists — they have depth of expertise in one area and knowledge of other closely related areas. NOTE: ML is an acronym for machine learning.

One of the first few posts I wrote when I first started writing was a collection of the different places I could be found on the internet. That post was more than five (!) years ago. The other day, I happened to come across that post almost by accident and actually, even though I wrote two ‘updates’ to that post, it turns out that I wrote a second post almost a year and a half after that. In looking at those posts, I thought it might be fun to write an update to the series.

Even though I’ve already written an updated post to the first post, I thought I’d still look back on some of the places I used to frequent in that very first post five years ago.

Five years ago, it looks like I had planned on developing a presence on YouTube:

I have a channel on YouTube where I upload videos of presentations. You’ll also find videos that I “like” on YouTube along with videos that I have commented on.

As it happens, there really isn’t much more to my YouTube profile than links back to other places you can find me. I do have some things on YouTube, but that’s only if you’re a student in one of my classes (and have access to the lectures I’ve uploaded).

Similarly, I used to do a lot of writing for Squidoo. It’s been so long since I’d visited any of the things I’d written for that site that it’s not even called Squidoo (!) anymore — HubPages acquired them.

I also let my BodyTalk certification lapse, as my career went in a different direction.

It looks like I used to be a frequent commenter at other sites. In particular, I had profiles with IntenseDebate and Disqus (two popular commenting services). It looks like I haven’t had a comment with either of those two services in more than 2 years (almost 3.5 years with IntenseDebate).

Lastly, I highlighted two Toronto sports blogs that I used to be an active member of: Bluebird Banter and Pension Plan Puppets. If I check-in on my comment history for both those sites, it won’t even let me discern when I last made a post (as it’s been that long).

~

If I look at the second post I wrote (in late 2012), the only carryover from the first post (of places I’m no longer that active) is the two commenting services: IntenseDebate and Disqus.

Now, let’s look at some of the places that I still frequent (in one way or another).

In that first post, I talked about writing posts (I’m nearly up to 600 on here). I also highlighted my LinkedIn profile (it’s up to date!), and my Twitter account (I like to share articles that I think people will find useful).

In the second post, I added two other places: Facebook and Quora. At the time, I used to be a frequent contributor to Facebook. Like Twitter, I liked to share articles that I thought people would find useful. I also liked to share pictures I found on the Internet that were either beautiful or provided a different perspective. Somewhere along the way, Facebook changed its algorithms and the people who “liked/followed” your page were no longer receiving all your updates. As a result, I stopped actively contributing in that environment. However, whenever I publish a new post, a link to that post is automatically uploaded to Facebook.

As for the second place — Quora — at the time, I did spend some time trying to build a presence on Quora. I wrote more than 60 answers, but it looks like I haven’t written anything for Quora in almost 3 years. I didn’t realize this until writing this post, but it looks like there are a number of answers that I’ve written for Quora that have more views than some of the things that I’ve written for this website.

~

So, in the last 3+ years, how have my internet frequenting habits changed? Well, the best place to find me is still here on this site. Twitter and LinkedIn are also places that I continue to update. Two new places: Business2Community and Research Blogging. Business 2 Community is one of the top business blogs and Research Blogging is a community and collection of posts written about academic research.

Last fall, I came across a post on Vox about high-speed rail. If you’ve read some of the things I published when I first started writing, you’ll know that I’m a big proponent of it. This post on Vox was meant to talk about some of the things that Americans can learn from Europeans when it comes to high-speed rail. In particular, California from Germany. The the part I want to focus on, though, is a paragraph with an historical perspective:

Europeans’ cities were more built up before the car, and they didn’t then tear their cities apart to accommodate cars and facilitate sprawl, as we did. The US is so vast that we could pave everything within 200 miles of New York City and still have more than enough land for our corn and cows. But if Europeans wanted to preserve rural areas, they would have to use urban space more efficiently, and so they have. A much greater share of the typical European metro area’s population is concentrated in its inner city. So you get dense, transit-rich cities with countryside in between.

When I first started writing about high-speed rail and even in that post I linked to in the second sentence of this post, I didn’t take into account the historical perspective. I did talk about land area, but the composition of that land area might be more important than the land area itself. If there isn’t the space “in the city” to put the high-speed rail, it’s going to take a yeomen’s effort and a healthy serving of political capital to create that space. The unfortunate part is, as time moves forward, the necessity (and gains!) of high-speed rail increase. The population of some of the biggest cities in the US (that would be served by better public transportation) is increasing and while I’m not sure the best way to measure it, I suspect that the business between cities (i.e. the necessity to travel between cities where high-speed rail would be beneficial) is probably increasing.

So, where does that leave high-speed rail proponents, aside from considering an extended trip to Europe? That’s a great question. It seems that there’s still going to be those organizations that lobby Congress, but if I had to hazard a guess (or a forecast, if you will), I suspect that the most likely way for there to be an improvement in high-speed rail in the US is some sort of catalyzing event. You might even call it a tipping point. One such way could be an increase in the cost of oil (i.e. jet fuel), skyrocketing the price of flying and forcing people to consider other modes of transportation from Chicago to New York. It might also be that a presidential candidate takes up the issue of public transportation and rides it as their “thing” to the White House (and then implements the plan within the first 100 days of office). Both of those scenarios aren’t very likely, but this pie-in-the-sky thinking is where high-speed rail proponents find themselves.

I like to think of myself as relatively computer literate. When I was in elementary school, I taught myself how to use HTML and created/designed my own website. I don’t know if I’ve linked to it on here, but it’s still functioning. Of course, I don’t remember the login or password for it, so there’s no way for me to edit it, but it’s really odd to remember back to where (and when) I was during the creation of it.

Since my GeoCities days, the internet has changed quite a bit. I’ve created a few websites (mostly with WordPress, either through the free version or through the version you need to download), but I wouldn’t — by any stretch of the imagination — say that this is a strength of mine. My skills here are basic, (but when compared to the average person, one might say that they’re a bit beyond basic).

As a tangent, this reminds me of something during my time as an psychology undergraduate. During the “capstone” course for that major, I remember the professor telling us that the department had majors take a test at the beginning and end of the program. They found something interesting: when students took the test at the end of the program, students were reporting that they knew less about psychology than when they started the degree. That is, one of the questions on the ‘pre-test’ was rate your level of understanding of psychology on a Likert scale (one to ten) and that same test appeared on the ‘post-test.’ The department was finding that the average score on the post-test for that question was lower than the average score on the pre-test. Why, you might ask?

Well, as students began to learn more about the subject of psychology, they realized just how vast a subject that it is and as a result, realized just how much they didn’t know about the subject. Food for thought.

Anyways, yes, technology.

Does the phrase “ALT+TAB” or “Command+TAB” mean anything to you? What about “CTRL+F” or “Command+F”?

I’m definitely part of the 10% of people who know about things like this, but I’m sure there are a whole host of things that computers and the internet can do that are unknown to me. On that note, I recently learned of something that my Mac can do that I had no idea it could do — convert to PDF.

All this time, I had been using various websites to do this for me, but as it turns out, a simple process and my Mac will do it for me. Who knew! I wonder what else my Mac can do.

A couple of weeks ago, there was a great article in Fast Company about President Obama’s initiative to bring the the technology used in the US bureaucracy into the 21st century. After reading it, there were a few things that came to mind, so I thought I’d write a post with some “Quick Thoughts” as I have in past instances for other events/articles.

1. The first thing that struck me was this idea that Silicon Valley wants to change the world. In particular, the idea that they “think” they are changing the world, but that they actually aren’t. It reminded me of the penultimate episode of Season 1 of “Silicon Valley,” the HBO series. In it, the show parodies Silicon Valley startups who purport to “change the world.” You can see part of it in the beginning of this clip:

In remembering this episode, I wonder if it was like this in previous generations. Obviously, the technology in previous generations was different, especially because companies like Google, Facebook, and Microsoft weren’t even conceived. In addition, “Silicon Valley” looked very different in the ’40s and ’50s than it did in the ’70s and the ’80s. Nonetheless, I wonder if there were idealistic twentysomethings trying to create things that would revolutionize the way something worked.

2. The second thing that came to mind was this idea that lawyers spend a couple yrs in DC between jobs. When I lived in the DC area, I remember one of the jokes being that DC has more lawyers per capita than any other city in the US and part of that was because of the government. It also reminded me of scene from The West Wing in Season 7 when Josh Lyman (who has a law degree) flies to California to recruit Sam Seaborn (who is a lawyer) to come work with him at the White House.

I think it’s a fantastic idea to recruit folks who are wizards with technology into highly placed government positions to help accelerate the transition for many government agencies. Goodness knows that the VA could use a technology-upgrade. In thinking about this idea, though, it made me wonder if there are other professions that could also do with a “stopover” of sorts in the government, contributing their unique skillsets to advancing the mission of the US government. Lawyers already make the most sense as they’re position to write/interpret laws, but what other professions would be well-suited for short stints in the government?

Scientists probably also make sense. I’m reminded of Patrick Dempsey’s character from Grey’s Anatomy (Derek Shepherd) who was working on a brain initiative. I’d imagine that scientists in other fields could also do well to spend some time in a government agency, but that’s not really outside the norm. Meaning, that’s already a career path that’s identified for scientists. I wonder, are there other professions for which working in DC is not something that’s on the radar.